Genome Announcement: Draft Genome Assembly of Heterodera humuli Generated Using Long-Read Sequencing

Abstract The hop cyst nematode, Heterodera humuli, is the most common plant-parasitic nematode associated with hop worldwide. This study reports the draft genome of H. humuli generated on the PacBio Sequel IIe System with the ultra-low DNA input HiFi sequencing method, and the corresponding genome annotation. This genome resource will help further studies on H. humuli and other cyst nematodes.

Cyst nematodes are considered the second most important plant-parasitic nematodes (PPNs) worldwide, with Globodera and Heterodera as the most important genera (Jones et al., 2013).These PPNs are important not only for the extensive crop loss they cause but also for their ability to survive for long periods of time (> 20 years) in soil without a suitable host (Wright and Perry, 2006).The genus Heterodera is divided into nine groups based on morphological and molecular information: Afenestrata, Avenae, Bifenestra, Cardiolata, Cyperi, Goettingiana, Humili, Sacchari, and Schachtii (Handoo and Subbotin, 2018).The hop cyst nematode, Heterodera humuli, is the most common PPN associated with hop worldwide.Heterodera humuli is commonly found in Washington, Idaho, and Oregon, the most important states for hop production in the U.S. (Darling et al., 2023).Despite the importance of the pest, very little molecular data is available for H. humuli, including a lack of genomic or transcriptomic resources.Of the 82 described Heterodera spp.there are only three publicly available genomes, two from the Schachtii group (H.glycines and H. schachtii), and one from the Goettingiana group (H.carotae) (Masonbrink et al., 2019;Siddique et al., 2022;Wram et al., 2022).Generating a high-quality genome of H. humuli will provide an important resource for research regarding the management of H. humuli and for a wider range of cyst nematode investigations.
In 2022, a hopyard in Salem, Oregon was sampled for H. humuli.Briefly, soil was collected from seven plots (five soil cores/plot) using a 2.5-cm-diameter soil probe with a probe length of 30 cm (JMC, Newton, IA).The soil was mixed and placed on an aluminum tray to dry it for at least one week in a greenhouse at the Nematology Lab at USDA-ARS-HCDPMRU in Corvallis, Oregon.Cysts were extracted from dried soil using the USDA-cyst extractor (Zasada et al., Genome announcement: Núñez-Rodríguez et al.

2019
). Cysts (n = 115) were handpicked, placed in a petri dish, and cut to release encysted eggs.The eggs were cleaned and transferred into a 1.5 ml Eppendorf tube then filled with water to a final volume of 0.5 ml.The total number of nematodes (eggs and second-stage juveniles) was determined by counting a subsample of 50 µl.Excess water was subsequently removed by centrifugation and aspiration to a final volume of approximately 50 µl.Nematodes were shipped overnight to the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaigne, Illinois on dry ice for DNA extraction and sequencing.DNA extraction was performed as in Arora et al. (2023).Briefly, high molecular weight DNA was extracted from a total of 10,200 nematodes with the MagAttract HMW DNA kit (Qiagen, Hilden, Germany).The High-Sensitivity dsDNA kit (ThermoFisher Scientific, Waltham, MA) was used to determine DNA concentration using a Qubit (Thermo Fisher Scientific).DNA integrity was assessed using a Femto Pulse system (Agilent, Santa Clara, CA).
Purified genomic DNA (5 ng) was sheared with Megaruptor 3 (Diagenode, Denville, NJ), amplified using the PacBio Ultra-Low DNA input kit following the company's protocol (Pacific Biosciences, Menlo Park, CA), and converted into a PacBio library with the SMRTbell Express Template Prep kit version 2.0 (PacBio Biosciences).Qubit was used for library quantification and Femto Pulse for fragment size distribution.Sequencing was carried out on 1 SMRT cell 8 M on a PacBio Sequel IIe system using the circular consensus sequencing (CCS) mode and a 30h movie time with default parameters (three minimum passes and a minimum accuracy of 99%).The sequencing yielded 14.9 GB of CCS data.The total number of reads was 2,800,608 with a mean read length of 5,327 bp.
PacBio HiFi reads were filtered with the GNU Awk program v.4.0.2 (http://www.gnu.org/licenses/) and reads less than 3 kb were removed leaving 1,791,046 reads for assembly.Hifiasm v.0.16.1-r375 (Cheng et al., 2021) with default parameters was used for genome assembly.Blobtools v.1.0(Laetsch and Blaxter, 2017) with default parameters used to visualize de novo assembled contigs based on the read coverage and GC content.To determine coverage, raw data was mapped to the de novo assembly using minimap2 with default parameters (Li, 2018).A phylum identification was given to each contig in the assembly based on BLAST similarity (E-value < 10e ).Reads belonging to contigs with >10X coverage and identified as Nematoda or with no assigned identity (no-hit) were used to reassemble the H. humuli genome using the Hifiasm v.0.16.1-r375 algorithm.Blobtools v.1.0was again used to visualize the re-assembly based on the read coverage and GC content as described previously.After the filtered assembly was complete, contigs identified as belonging to the phylum Nematoda or with no identity (1,487 contigs out of 1,489 contigs) were retained to make the final genome assembly for H. humuli.The Blobtools visualizations of the meta and final assemblies are in Supplemental Figs. 1  and 2, respectively.Genome statistics (Table 1) were obtained using QUAST 5.2.0 default parameters (Gurevich et al., 2013).
The objective of this genome sequencing effort was to provide high quality reference data to expand the publicly available genomic resources for cyst nematodes.The assembled genome size of H. humuli is 90,806,450 bp in a total of 1,487 contigs (Table 1) with an average 112X coverage.The genome provided in this study is smaller than the other available Heterodera spp.genomes, up to ~ 100 Mb less when compared to the H. schachtii genome (Table 1).The potential genome size and repeat length for H. humuli are estimated to be 90,077,635 and 63,372,724 bp, respectively, by using reads > 3 kb as input and a kmer size of 21 in GenomeScope (Vurture et al., 2017).The assembly has a GC content of 36.11% and a N50 of 111,383 bp (Table 1).
Completeness of the assembly of H. humuli and the genomes of the three Heterodera spp.mentioned above was determined with BUSCO v5.4.5 using the eukaryota_odb10 and nematoda_odb10 databases (Manni et al., 2021) (Supplementary Fig. 3).Heterodera humuli had the second and third most complete number of BUSCO genes when using the eukaryota_odb10 and nematoda_odb10 databases, respectively (Supplementary Fig. 3).
To annotate the genome of H. humuli, highly repetitive regions were identified and masked using RepeatModeler v 2.0.2 and RepeatMasker v 4.1.0,respectively, using default parameters (Smit and Hubley, 2015a;Smit and Hubley, 2015b).Predicted proteins from the H. glycines genome (Masonbrink et al., 2019) were used as protein hints to annotate the masked genome with BRAKER3 v 3.0.3using default parameters (Lomsadze et al., 2005;Stanke et al., 2006;Gotoh, 2008;Stanke et al., 2008 and Gotoh, 2012; Buchfink et al., 2015;Hoff et al., 2016;Hoff et al., 2019;Bruna et al., 2020;Bruna et al., 2021).In general, H. humuli has a smaller number of predicted number of transcripts compared to the other Heterodera species included in this analysis.When compared to H. schachtii, H. humuli has 14,716 fewer transcripts (Table 1).The BUSCO analysis was also performed on the predicted proteins from all Heteredora spp.included in this study using both the nematoda_odb10 and eukaryota_odb10 databases.Heterodera humuli had the second highest complete BUSCO score with both the nematoda_odb10 (64.9 %) and eukaryota_odb10 (86.6 %) databases (Table 1).
The partial mitochondrial cox1 gene was retrieved from the H. humuli assembly using usearch11 (Edgar, 2010) with the H. humili accession number ON007077 from NCBI.Other cox1 sequences from Heterodera spp.were retrieved from NCBI, along with outgroup Rotylenchus spp., to perform a phylogenetic analysis.Sequences were aligned with the Clustal W algorithm with default parameters (Thompson et al., 1994) and trimmed using BioEdit v.7.0.5.3 (Hall, 1999).The best substitution model was determined using jModelTest 2.1.10v20160303 with default parameters (Darriba et al., 2012) and a Bayesian phylogenetic inference was performed using MrBayes v3.2 (Ronquist et al., 2012) at the CyberInfrastructure for Phylogenetic Research (CIPRES) Science Gateway (Miller et al., 2010) with default parameters.Subsequently, FigTree v1.4.3 (Rambaut, 2016) was used to visualize the resulting phylogenetic tree.The phylogenetic analysis placed the cox1 sequence from this H. humuli assembly (coded as ptg000050c_HCN) in a clade with other H. humuli sequences with a posterior probability value of 100% (Supplementary Fig. 4).Thus, confirming the identity of the species.
Genome assembly, annotation, and raw data for H. humuli can be found at NCBI under the BioProject number PRJNA1048471 (BioSample number SAMN38640877).This genome of H. humili generated using long reads offers a valuable genetic resource for future research efforts on the biology of H. humuli, discovery of novel effectors, genomic comparison among cyst forming nematodes, and many other aspects.(Hall, 1999).The best substitution model was determined using jModelTest 2.1.10v20160303 (Darriba et al., 2012) and the Bayesian analysis was performed using MrBayes v3.2 (Ronquist et al., 2012) at the CIPRES Science Gateway. Finally, FigTree v1.4.3 (Rambaut, 2016) was used to visualize the resulting phylogenetic tree.

Figure S4 .
Figure S4.Phylogenetic relationships between Heterodera species as inferred from Bayesian analysis of the partial cox1 gene sequences under the GTR + I + G model.Posterior probability values are given for appropriate clades.The bold name represents the H. humuli sequence derived from this study.Sequences were retrieved from GenBank, aligned, and trimmed with BioEdit v.7.0.5.3(Hall, 1999).The best substitution model was determined using jModelTest 2.1.10v20160303(Darriba et al., 2012) and the Bayesian analysis was performed using MrBayes v3.2(Ronquist et al., 2012)  at the CIPRES Science Gateway.Finally, FigTree v1.4.3 (Rambaut, 2016) was used to visualize the resulting phylogenetic tree.

Table 1 .
; Iwata Comparison of genome assembly statistics of x NCBI GenBank BioProject number.